Sampling With Synthesis: A New Approach for Releasing Public Use Census Microdata
Sampling With Synthesis: A New Approach for Releasing Public Use Census Microdata
复制标题
DOI：
10.1198/jasa.2010.ap09480
复制
发表时间：
2010-12-01
影响因子：
3.7
通讯作者：
Reiter, Jerome P.
中科院分区：
文献类型：
--
作者：
Drechsler, Jorg;Reiter, Jerome P.
许多统计机构向公众散发普查微数据样本，即个人记录的数据。在发布微数据之前，机构通常会更改识别值或敏感值以保护数据主体的机密性，例如通过粗化、干扰或交换数据。这些标准的披露限制技术扭曲了原始数据中的关系和分布特征，特别是在高强度应用时。此外，被掩盖的公众使用数据的分析人员很难根据披露限制的影响调整推断。基于这些不足，我们提出了一种称为综合抽样的人口普查微数据传播方法。其基本思想是将人口普查中的识别值或敏感值替换为多重输入，并从这些多重输入的人口中释放样本。我们证明，与标准统计披露限制的抽样相比，采用综合抽样可以提高公共使用数据的质量；仿真结果表明，这是在线提供的补充材料。我们推导了用合成方法分析由采样产生的多数据集的方法。我们提出了基于披露风险和数据效用的考虑来选择要综合的普查值的算法。我们用美国当前人口调查的数据构建了一个人口，用合成来说明抽样。
Many statistical agencies disseminate samples of census microdata, that is, data on individual records, to the public. Before releasing the microdata, agencies typically alter identifying or sensitive values to protect data subjects' confidentiality, for example by coarsening, perturbing, or swapping data. These standard disclosure limitation techniques distort relationships and distributional features in the original data, especially when applied with high intensity. Furthermore, it can be difficult for analysts of the masked public use data to adjust inferences for the effects of the disclosure limitation. Motivated by these shortcomings, we propose an approach to census microdata dissemination called sampling with synthesis. The basic idea is to replace the identifying or sensitive values in the census with multiple imputations, and release samples from these multiply-imputed populations. We demonstrate that sampling with synthesis can improve the quality of public use data relative to sampling followed by standard statistical disclosure limitation; simulation results showing this are available online as supplemental material. We derive methods for analyzing the multiple datasets generated by sampling with synthesis. We present algorithms for selecting which census values to synthesize based on considerations of disclosure risk and data utility. We illustrate sampling with synthesis on a population constructed with data from the U.S. Current Population Survey.